Sensitivity and spectral control of network lasers

Recently, random lasing in complex networks has shown efficient lasing over more than 50 localised modes, promoted by multiple scattering over the underlying graph. If controlled, these network lasers can lead to fast-switching multifunctional light sources with synthesised spectrum. Here, we observe both in experiment and theory high sensitivity of the network laser spectrum to the spatial shape of the pump profile, with some modes for example increasing in intensity by 280% when switching off 7% of the pump beam. We solve the nonlinear equations within the steady state ab-initio laser theory (SALT) approximation over a graph and we show selective lasing of around 90% of the strongest intensity modes, effectively programming the spectrum of the lasing networks. In our experiments with polymer networks, this high sensitivity enables control of the lasing spectrum through non-uniform pump patterns. We propose the underlying complexity of the network modes as the key element behind efficient spectral control opening the way for the development of optical devices with wide impact for on-chip photonics for communication, sensing, and computation. Nanophotonic light sources with programmable emission spectrum are important building blocks for integrated photonics, sensing and optical computing. Here the authors tune the complex laser spectrum of a network laser achieving selective lasing of a single, two or more modes.

Automated summary

Recent research has shown that random lasing in complex networks can achieve efficient lasing properties and fast-switching multifunctional light sources by controlling the spatial shape of the pump profile. By solving nonlinear equations within the network graph and selectively lasing the strongest intensity modes, the spectrum of the lasing networks can be effectively programmed. This high sensitivity allows for control of the lasing spectrum through non-uniform pump patterns, leading to the development of optical devices with wide impact for on-chip photonics for communication, sensing, and computation.